a test for log length consistency

tests/callbacks/test_callbacks.py

@@ -355,3 +355,29 @@ def test_lr_logger_param_groups(tmpdir):
         'Number of learning rates logged does not match number of param groups'
     assert all([k in ['lr-Adam/pg1', 'lr-Adam/pg2'] for k in lr_logger.lrs.keys()]), \
         'Names of learning rates not set correctly'
+
+
+def test_lr_logger_multiple_schedulers(tmpdir):
+    """ Test that learning rates are extracted and logged for single lr scheduler"""
+    tutils.reset_seed()
+
+    model = EvalModelTemplate()
+    model.configure_optimizers = model.configure_optimizers__multiple_schedulers
+
+    lr_logger = LearningRateLogger()
+    trainer = Trainer(
+        default_root_dir=tmpdir,
+        max_epochs=5,
+        val_percent_check=0.1,
+        train_percent_check=0.5,
+        callbacks=[lr_logger]
+    )
+    results = trainer.fit(model)
+
+    assert lr_logger.lrs, 'No learning rates logged'
+    assert len(lr_logger.lrs) == len(trainer.lr_schedulers), \
+        'Number of learning rates logged does not match number of param groups'
+    assert all([k in ['lr-Adam', 'lr-Adam-1'] for k in lr_logger.lrs.keys()]), \
+        'Names of learning rates not set correctly'
+    assert all(len(lr) == 5 for k, lr in lr_logger.lrs.items()), \
+        'Inconsistent learning rate log'